* add more docs
* add more docs
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* Update train.py
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* Implementation of Early Stopping for DDP training
This edit correctly uses the broadcast_object_list() function to send slave processes a boolean so to end the training phase if the variable is True, thus allowing the master process to destroy the process group and terminate.
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* Update train.py
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* Update train.py
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* Update train.py
* Further cleanup
This cleans up the definition of broadcast_list and removes the requirement for clear() afterward.
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* Add filesize to benchmarks.py
* Add filesize to benchmarks.py
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* Create README_cn.md
Add mandarin version of README
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* remove line
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* Kiera fix
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* HUB dataset_stats() error reporting
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* Update dataloaders.py
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* Reject webcam inference on Colab/Kaggle
Improve user error understanding for https://github.com/ultralytics/yolov5/issues/8180
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* cleanup
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* AutoBatch checks against failed solutions
@kalenmike this is a simple improvement to AutoBatch to verify that returned solutions have not already failed, i.e. return batch-size 8 when 8 already produced CUDA out of memory.
This is a halfway fix until I can implement a 'final solution' that will actively verify the solved-for batch size rather than passively assume it works.
* Update autobatch.py
* Update autobatch.py